A Practical Reflectance Transformation Imaging Pipeline for Surface Characterization in Cultural Heritage

We present a practical acquisition and processing pipeline to characterize the surface structure of cultural heritage objects. Using a free-form Reflectance Transformation Imaging (RTI) approach, we acquire multiple digital photographs of the studied object shot from a stationary camera. In each photograph, a light is freely positioned around the object in order to cover a wide variety of illumination directions. Multiple reflective spheres and white Lambertian surfaces are added to the scene to automatically recover light positions and to compensate for non-uniform illumination. An estimation of geometry and reflectance parameters (e.g., albedo, normals, polynomial texture maps coefficients) is then performed to locally characterize surface properties. The resulting object description is stable and representative enough of surface features to reliably provide a characterization of measured surfaces. We validate our approach by comparing RTI-acquired data with data acquired with a high-resolution microprofilometer.Terms: "European Union (EU)" & "Horizon 2020" / Action: H2020-EU.3.6.3. - Reflective societies - cultural heritage and European identity / Acronym: Scan4Reco / Grant number: 66509

Base materials for photometric stereo

Image-based capture of material appearance has been extensively studied, but the quality of the results and generality of the applied methods leave a lot of room for improvement. Most existing methods rely on parametric models of reflectance and require complex hardware systems or accurate geometric models that are not always available or practical. Rather than independently estimating reflectance properties for each surface point, it is common to express the reflectance as a combination of base materials inherent to each particular object or scene. We propose a method for efficient and automatic extraction of base materials in a photometric stereo system. After jointly estimating per-pixel reflectances and refined surface normals using these materials, we can render photo-realistic images of complex objects under novel lighting conditions in real time. © 2012 Springer-Verlag.Tingdahl D., Godau C., Van Gool L., ''Base materials for photometric stereo'', Lecture notes in computer science, vol. 7584, pp. 350-359, 2012 (4th color and photometry in computer vision workshop - CPCV-2012, in conjuction with ECCV 2012, October 13, 2012, Firenze, Italy).status: publishe